Triple

T25773711
Position Surface form Disambiguated ID Type / Status
Subject Toni Ko E649087 entity
Predicate entrepreneurialReputation P87297 FINISHED
Object self-made beauty entrepreneur LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: self-made beauty entrepreneur | Statement: [Toni Ko, entrepreneurialReputation, self-made beauty entrepreneur]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: entrepreneurialReputation
Context triple: [Toni Ko, entrepreneurialReputation, self-made beauty entrepreneur]
  • A. commercialReputation
    Indicates the perceived standing or esteem of an entity in a commercial or business context, based on others’ experiences, opinions, or evaluations.
  • B. hasProfessionalReputationFor chosen
    Indicates that an entity is recognized by others as being notably associated with a particular professional quality, skill, or behavior.
  • C. reputationBuiltFor
    Indicates that one entity has established or developed a reputation specifically for or in relation to another entity.
  • D. internationalReputation
    Indicates the recognized standing, esteem, or status an entity holds within the global or international community.
  • E. institutionalReputationContext
    Indicates the situational or environmental factors that shape or influence an institution’s reputation.
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e7ab333b508190b6d708d8d9a328ed completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f5fe5b23ac81908ff1b6f06911f45b completed May 2, 2026, 1:38 p.m.
PD Predicate disambiguation batch_69f4a0fed15881909b789251fe5d8d45 completed May 1, 2026, 12:47 p.m.
Created at: April 22, 2026, 5:32 a.m.